Is it harmful to set the learning rate of training a model to be too high if there is some decay function for the learning rate?
Setting too high a learning rate will extend the time to get a good result.

In my opinion, it is better to set not too big a learning rate but to use learning with momentum. When the learning starts to be ineffective, increase the learning rate to find a better optimal result. It seems to me that this allows to get very good results in a faster time than setting a large value of the learning rate from the very beginning. At least in cases I've dealt with.